Exemplo n.º 1
0
    def _calibData(self, sam_ws, mon_ws):
        api.MaskDetectors(Workspace=sam_ws, DetectorList=self._dMask)
        #MaskedWorkspace='BASIS_MASK')
        api.ModeratorTzeroLinear(InputWorkspace=sam_ws,\
                           OutputWorkspace=sam_ws)
        api.LoadParameterFile(Workspace=sam_ws,
                              Filename=config.getInstrumentDirectory() +
                              'BASIS_silicon_111_Parameters.xml')
        api.ConvertUnits(InputWorkspace=sam_ws,
                         OutputWorkspace=sam_ws,
                         Target='Wavelength',
                         EMode='Indirect')

        if not self._noMonNorm:
            api.ModeratorTzeroLinear(InputWorkspace=mon_ws,\
                               OutputWorkspace=mon_ws)
            api.Rebin(InputWorkspace=mon_ws,
                      OutputWorkspace=mon_ws,
                      Params='10')
            api.ConvertUnits(InputWorkspace=mon_ws,
                             OutputWorkspace=mon_ws,
                             Target='Wavelength')
            api.OneMinusExponentialCor(InputWorkspace=mon_ws,
                                       OutputWorkspace=mon_ws,
                                       C='0.20749999999999999',
                                       C1='0.001276')
            api.Scale(InputWorkspace=mon_ws,
                      OutputWorkspace=mon_ws,
                      Factor='9.9999999999999995e-07')
            api.RebinToWorkspace(WorkspaceToRebin=sam_ws,
                                 WorkspaceToMatch=mon_ws,
                                 OutputWorkspace=sam_ws)
            api.Divide(LHSWorkspace=sam_ws,
                       RHSWorkspace=mon_ws,
                       OutputWorkspace=sam_ws)
Exemplo n.º 2
0
    def _calibData(self, sam_ws, mon_ws):
        sapi.MaskDetectors(Workspace=sam_ws,
                           DetectorList=self._dMask)
        sapi.ModeratorTzeroLinear(InputWorkspace=sam_ws,
                                  OutputWorkspace=sam_ws)
        sapi.LoadParameterFile(Workspace=sam_ws,
                               Filename=pjoin(DEFAULT_CONFIG_DIR,
                                              self._reflection["parameter_file"]))
        sapi.ConvertUnits(InputWorkspace=sam_ws,
                          OutputWorkspace=sam_ws,
                          Target='Wavelength',
                          EMode='Indirect')

        if self._MonNorm:
            sapi.ModeratorTzeroLinear(InputWorkspace=mon_ws,
                                      OutputWorkspace=mon_ws)
            sapi.Rebin(InputWorkspace=mon_ws,
                       OutputWorkspace=mon_ws,
                       Params='10')
            sapi.ConvertUnits(InputWorkspace=mon_ws,
                              OutputWorkspace=mon_ws,
                              Target='Wavelength')
            sapi.OneMinusExponentialCor(InputWorkspace=mon_ws,
                                        OutputWorkspace=mon_ws,
                                        C='0.20749999999999999',
                                        C1='0.001276')
            sapi.Scale(InputWorkspace=mon_ws,
                       OutputWorkspace=mon_ws,
                       Factor='1e-06')
            sapi.RebinToWorkspace(WorkspaceToRebin=sam_ws,
                                  WorkspaceToMatch=mon_ws,
                                  OutputWorkspace=sam_ws)
            sapi.Divide(LHSWorkspace=sam_ws,
                        RHSWorkspace=mon_ws,
                        OutputWorkspace=sam_ws)
Exemplo n.º 3
0
    def _generate_flux_spectrum(self, run_set, sam_ws):
        r"""
        Retrieve the aggregate flux and create an spectrum of intensities
        versus wavelength such that intensities will be similar for any
        of the possible flux normalization types.

        Parameters
        ----------
        sam_ws: str
            Name of aggregated sample workspace

        Returns
        -------
        str
            Name of aggregated flux workspace (output workspace)
        """

        flux_binning = [1.5, 0.0005, 7.5]  # wavelength binning
        suffix = re.sub('[^0-9a-zA-Z]+', '_', self._flux_normalization_type)
        flux_ws = tws(self._make_run_name(run_set[0]) + '_' + suffix)
        if self._MonNorm:
            self._sum_monitors(run_set, flux_ws)
            rpf = self._elucidate_reflection_parameter_file(sam_ws)
            sapi.LoadParameterFile(Workspace=flux_ws, Filename=rpf)
            sapi.ModeratorTzeroLinear(InputWorkspace=flux_ws,
                                      OutputWorkspace=flux_ws)
            sapi.Rebin(InputWorkspace=flux_ws,
                       OutputWorkspace=flux_ws,
                       Params='10',  # 10 microseconds TOF bin width
                       PreserveEvents=False)
            sapi.ConvertUnits(InputWorkspace=flux_ws,
                              OutputWorkspace=flux_ws,
                              Target='Wavelength')
            sapi.OneMinusExponentialCor(InputWorkspace=flux_ws,
                                        OutputWorkspace=flux_ws,
                                        C='0.20749999999999999',
                                        C1='0.001276')
            sapi.Scale(InputWorkspace=flux_ws, OutputWorkspace=flux_ws,
                       Factor='1e-06')
            sapi.Rebin(InputWorkspace=flux_ws, OutputWorkspace=flux_ws,
                       Params=flux_binning)
        else:
            ws = mtd[sam_ws].getRun()
            if self._flux_normalization_type == 'Proton Charge':
                aggregate_flux = ws.getProtonCharge()
            elif self._flux_normalization_type == 'Duration':
                aggregate_flux = ws.getProperty('duration').value
            # These factors ensure intensities typical of flux workspaces
            # derived from monitor data
            f = {'Proton Charge': 0.00874, 'Duration': 0.003333}
            x = np.arange(flux_binning[0], flux_binning[2], flux_binning[1])
            y = f[self._flux_normalization_type] * \
                aggregate_flux * np.ones(len(x) - 1)
            _flux_ws = sapi.CreateWorkspace(OutputWorkspace=flux_ws, DataX=x,
                                            DataY=y, UnitX='Wavelength')
            _flux_ws.setYUnit(mtd[sam_ws].YUnit())
        return flux_ws
Exemplo n.º 4
0
 def _calibrate_data(self, run_set, sam_ws):
     sapi.MaskDetectors(Workspace=sam_ws, DetectorList=self._dMask)
     rpf = self._elucidate_reflection_parameter_file(sam_ws)
     sapi.LoadParameterFile(Workspace=sam_ws, Filename=rpf)
     sapi.ModeratorTzeroLinear(InputWorkspace=sam_ws,
                               OutputWorkspace=sam_ws)
     sapi.ConvertUnits(InputWorkspace=sam_ws,
                       OutputWorkspace=sam_ws,
                       Target='Wavelength', EMode='Indirect')
     if self._flux_normalization_type is not None:
         flux_ws = self._generate_flux_spectrum(run_set, sam_ws)
         sapi.RebinToWorkspace(WorkspaceToRebin=sam_ws,
                               WorkspaceToMatch=flux_ws,
                               OutputWorkspace=sam_ws)
         sapi.Divide(LHSWorkspace=sam_ws, RHSWorkspace=flux_ws,
                     OutputWorkspace=sam_ws)